hbos.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "hbos_SabyasachiDatta_OPD2009.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "UlD6-56pwQXd"
      },
      "source": [
        "from sklearn.datasets import load_iris\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 59,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HICN7cx8w6zu"
      },
      "source": [
        "data = load_iris().data"
      ],
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xWouwc33x_Bu"
      },
      "source": [
        "names = ['sepal-length', 'sepal-width', 'petal-length', 'petal-width']"
      ],
      "execution_count": 61,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2ZVMF480yjiL"
      },
      "source": [
        "df = pd.DataFrame(data,columns=names)"
      ],
      "execution_count": 62,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "Y3j4JG0dzpyV",
        "outputId": "09954c96-18a5-41b7-86ba-121e8ae3e36b"
      },
      "source": [
        "df"
      ],
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sepal-length</th>\n",
              "      <th>sepal-width</th>\n",
              "      <th>petal-length</th>\n",
              "      <th>petal-width</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>5.1</td>\n",
              "      <td>3.5</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>4.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>4.7</td>\n",
              "      <td>3.2</td>\n",
              "      <td>1.3</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.6</td>\n",
              "      <td>3.1</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
              "      <td>3.6</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>6.7</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.2</td>\n",
              "      <td>2.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>6.3</td>\n",
              "      <td>2.5</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>6.5</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.2</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>6.2</td>\n",
              "      <td>3.4</td>\n",
              "      <td>5.4</td>\n",
              "      <td>2.3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>5.9</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.1</td>\n",
              "      <td>1.8</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     sepal-length  sepal-width  petal-length  petal-width\n",
              "0             5.1          3.5           1.4          0.2\n",
              "1             4.9          3.0           1.4          0.2\n",
              "2             4.7          3.2           1.3          0.2\n",
              "3             4.6          3.1           1.5          0.2\n",
              "4             5.0          3.6           1.4          0.2\n",
              "..            ...          ...           ...          ...\n",
              "145           6.7          3.0           5.2          2.3\n",
              "146           6.3          2.5           5.0          1.9\n",
              "147           6.5          3.0           5.2          2.0\n",
              "148           6.2          3.4           5.4          2.3\n",
              "149           5.9          3.0           5.1          1.8\n",
              "\n",
              "[150 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 101
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 381
        },
        "id": "uDnrgtf2zyT-",
        "outputId": "d8752ef6-1f0f-4cbe-dfe4-43941ebc8bc7"
      },
      "source": [
        "plt.figure(figsize=[10,10])\n",
        "f,a = plt.subplots(2,2)\n",
        "a = a.ravel()\n",
        "\n",
        "count = []\n",
        "binning = []\n",
        "# density=True - normaloize the histogram\n",
        "for id,ax in enumerate(a):\n",
        "    counts, bins, patches = ax.hist(dataset.iloc[:,id], bins=4,density=True, color='#0504aa',alpha=0.7, rwidth=0.85)\n",
        "    count.append(counts)\n",
        "    binning.append(bins)\n",
        "    print(counts, bins)\n",
        "    ax.set_title(dataset.columns[id])\n",
        "plt.tight_layout()"
      ],
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[0.3037037  0.35555556 0.35555556 0.0962963 ] [4.3 5.2 6.1 7.  7.9]\n",
            "[0.21111111 0.83333333 0.55555556 0.06666667] [2.  2.6 3.2 3.8 4.4]\n",
            "[0.2259887  0.04971751 0.27570621 0.12655367] [1.    2.475 3.95  5.425 6.9  ]\n",
            "[0.55555556 0.16666667 0.56666667 0.37777778] [0.1 0.7 1.3 1.9 2.5]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C4hETldFJmIC"
      },
      "source": [
        "#count stores the bin frequency\n",
        "iris = pd.DataFrame()"
      ],
      "execution_count": 103,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ESKGpPmmIXz7"
      },
      "source": [
        "iris['sepal_newLenght'] = pd.cut(x=dataset['sepal_length'], bins=4, labels=count[0], include_lowest=True, ordered=False)\n",
        "iris['sepal_newWeight'] =  pd.cut(x=dataset['sepal_width'], bins=4, labels=count[1], include_lowest=True, ordered=False)\n",
        "iris['petal_newLenght'] = pd.cut(x=dataset['petal_length'], bins=4, labels=count[2], include_lowest=True, ordered=False)\n",
        "iris['petal_newWeight'] =  pd.cut(x=dataset['petal_width'], bins=4, labels=count[3], include_lowest=True, ordered=False)"
      ],
      "execution_count": 104,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "ZxHnMghUpvsH",
        "outputId": "026ea55e-44f6-4beb-f4d4-29c266cff192"
      },
      "source": [
        "iris"
      ],
      "execution_count": 105,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sepal_newLenght</th>\n",
              "      <th>sepal_newWeight</th>\n",
              "      <th>petal_newLenght</th>\n",
              "      <th>petal_newWeight</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.303704</td>\n",
              "      <td>0.555556</td>\n",
              "      <td>0.225989</td>\n",
              "      <td>0.555556</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.303704</td>\n",
              "      <td>0.833333</td>\n",
              "      <td>0.225989</td>\n",
              "      <td>0.555556</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.303704</td>\n",
              "      <td>0.833333</td>\n",
              "      <td>0.225989</td>\n",
              "      <td>0.555556</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.303704</td>\n",
              "      <td>0.833333</td>\n",
              "      <td>0.225989</td>\n",
              "      <td>0.555556</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.303704</td>\n",
              "      <td>0.555556</td>\n",
              "      <td>0.225989</td>\n",
              "      <td>0.555556</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>0.355556</td>\n",
              "      <td>0.833333</td>\n",
              "      <td>0.275706</td>\n",
              "      <td>0.377778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>0.355556</td>\n",
              "      <td>0.211111</td>\n",
              "      <td>0.275706</td>\n",
              "      <td>0.566667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>0.355556</td>\n",
              "      <td>0.833333</td>\n",
              "      <td>0.275706</td>\n",
              "      <td>0.377778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>0.355556</td>\n",
              "      <td>0.555556</td>\n",
              "      <td>0.275706</td>\n",
              "      <td>0.377778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>0.355556</td>\n",
              "      <td>0.833333</td>\n",
              "      <td>0.275706</td>\n",
              "      <td>0.566667</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    sepal_newLenght sepal_newWeight petal_newLenght petal_newWeight\n",
              "0          0.303704        0.555556        0.225989        0.555556\n",
              "1          0.303704        0.833333        0.225989        0.555556\n",
              "2          0.303704        0.833333        0.225989        0.555556\n",
              "3          0.303704        0.833333        0.225989        0.555556\n",
              "4          0.303704        0.555556        0.225989        0.555556\n",
              "..              ...             ...             ...             ...\n",
              "145        0.355556        0.833333        0.275706        0.377778\n",
              "146        0.355556        0.211111        0.275706        0.566667\n",
              "147        0.355556        0.833333        0.275706        0.377778\n",
              "148        0.355556        0.555556        0.275706        0.377778\n",
              "149        0.355556        0.833333        0.275706        0.566667\n",
              "\n",
              "[150 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 105
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fcHdb4-IJs7B"
      },
      "source": [
        "iris = iris.astype(float)"
      ],
      "execution_count": 106,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wfphJlGxKY7n"
      },
      "source": [
        "# Divide each column with sum of frequencies of histogram\n",
        "iris['sepal_newLenght'] = iris['sepal_newLenght'].div(sum(count[0]))\n",
        "iris['sepal_newWeight'] = iris['sepal_newWeight'].div(sum(count[1]))\n",
        "iris['petal_newLenght'] = iris['petal_newLenght'].div(sum(count[2]))\n",
        "iris['petal_newWeight'] = iris['petal_newWeight'].div(sum(count[3]))"
      ],
      "execution_count": 107,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "P3eto5-MPdmD",
        "outputId": "a79a73fd-9ecf-4086-864c-51fcd5facdf2"
      },
      "source": [
        "iris"
      ],
      "execution_count": 108,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sepal_newLenght</th>\n",
              "      <th>sepal_newWeight</th>\n",
              "      <th>petal_newLenght</th>\n",
              "      <th>petal_newWeight</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.273333</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.273333</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.273333</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.273333</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.273333</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.333333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>0.320000</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.406667</td>\n",
              "      <td>0.226667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>0.320000</td>\n",
              "      <td>0.126667</td>\n",
              "      <td>0.406667</td>\n",
              "      <td>0.340000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>0.320000</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.406667</td>\n",
              "      <td>0.226667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>0.320000</td>\n",
              "      <td>0.333333</td>\n",
              "      <td>0.406667</td>\n",
              "      <td>0.226667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>0.320000</td>\n",
              "      <td>0.500000</td>\n",
              "      <td>0.406667</td>\n",
              "      <td>0.340000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     sepal_newLenght  sepal_newWeight  petal_newLenght  petal_newWeight\n",
              "0           0.273333         0.333333         0.333333         0.333333\n",
              "1           0.273333         0.500000         0.333333         0.333333\n",
              "2           0.273333         0.500000         0.333333         0.333333\n",
              "3           0.273333         0.500000         0.333333         0.333333\n",
              "4           0.273333         0.333333         0.333333         0.333333\n",
              "..               ...              ...              ...              ...\n",
              "145         0.320000         0.500000         0.406667         0.226667\n",
              "146         0.320000         0.126667         0.406667         0.340000\n",
              "147         0.320000         0.500000         0.406667         0.226667\n",
              "148         0.320000         0.333333         0.406667         0.226667\n",
              "149         0.320000         0.500000         0.406667         0.340000\n",
              "\n",
              "[150 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UzAz9iCdhqat"
      },
      "source": [
        "iris = 1/iris"
      ],
      "execution_count": 109,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "Ec9Z2UxiiCtm",
        "outputId": "3db0feda-a64f-44ea-e42d-ba202ce26388"
      },
      "source": [
        "iris"
      ],
      "execution_count": 110,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sepal_newLenght</th>\n",
              "      <th>sepal_newWeight</th>\n",
              "      <th>petal_newLenght</th>\n",
              "      <th>petal_newWeight</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3.658537</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3.658537</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.658537</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3.658537</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3.658537</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>3.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>3.125000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.459016</td>\n",
              "      <td>4.411765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>3.125000</td>\n",
              "      <td>7.894737</td>\n",
              "      <td>2.459016</td>\n",
              "      <td>2.941176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>3.125000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.459016</td>\n",
              "      <td>4.411765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>3.125000</td>\n",
              "      <td>3.000000</td>\n",
              "      <td>2.459016</td>\n",
              "      <td>4.411765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>3.125000</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>2.459016</td>\n",
              "      <td>2.941176</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     sepal_newLenght  sepal_newWeight  petal_newLenght  petal_newWeight\n",
              "0           3.658537         3.000000         3.000000         3.000000\n",
              "1           3.658537         2.000000         3.000000         3.000000\n",
              "2           3.658537         2.000000         3.000000         3.000000\n",
              "3           3.658537         2.000000         3.000000         3.000000\n",
              "4           3.658537         3.000000         3.000000         3.000000\n",
              "..               ...              ...              ...              ...\n",
              "145         3.125000         2.000000         2.459016         4.411765\n",
              "146         3.125000         7.894737         2.459016         2.941176\n",
              "147         3.125000         2.000000         2.459016         4.411765\n",
              "148         3.125000         3.000000         2.459016         4.411765\n",
              "149         3.125000         2.000000         2.459016         2.941176\n",
              "\n",
              "[150 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 110
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UwixOOmViA0C"
      },
      "source": [
        "iris = np.log10(iris)"
      ],
      "execution_count": 111,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "WWcuuYzAiJYP",
        "outputId": "b0cf23c8-ffa3-4694-92f4-2cbeb137fce1"
      },
      "source": [
        "np.log10(iris)"
      ],
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sepal_newLenght</th>\n",
              "      <th>sepal_newWeight</th>\n",
              "      <th>petal_newLenght</th>\n",
              "      <th>petal_newWeight</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-0.249255</td>\n",
              "      <td>-0.321371</td>\n",
              "      <td>-0.321371</td>\n",
              "      <td>-0.321371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>-0.249255</td>\n",
              "      <td>-0.521390</td>\n",
              "      <td>-0.321371</td>\n",
              "      <td>-0.321371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>-0.249255</td>\n",
              "      <td>-0.521390</td>\n",
              "      <td>-0.321371</td>\n",
              "      <td>-0.321371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>-0.249255</td>\n",
              "      <td>-0.521390</td>\n",
              "      <td>-0.321371</td>\n",
              "      <td>-0.321371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>-0.249255</td>\n",
              "      <td>-0.321371</td>\n",
              "      <td>-0.321371</td>\n",
              "      <td>-0.321371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>-0.305526</td>\n",
              "      <td>-0.521390</td>\n",
              "      <td>-0.408088</td>\n",
              "      <td>-0.190701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>-0.305526</td>\n",
              "      <td>-0.047044</td>\n",
              "      <td>-0.408088</td>\n",
              "      <td>-0.329271</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>-0.305526</td>\n",
              "      <td>-0.521390</td>\n",
              "      <td>-0.408088</td>\n",
              "      <td>-0.190701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>-0.305526</td>\n",
              "      <td>-0.321371</td>\n",
              "      <td>-0.408088</td>\n",
              "      <td>-0.190701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>-0.305526</td>\n",
              "      <td>-0.521390</td>\n",
              "      <td>-0.408088</td>\n",
              "      <td>-0.329271</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     sepal_newLenght  sepal_newWeight  petal_newLenght  petal_newWeight\n",
              "0          -0.249255        -0.321371        -0.321371        -0.321371\n",
              "1          -0.249255        -0.521390        -0.321371        -0.321371\n",
              "2          -0.249255        -0.521390        -0.321371        -0.321371\n",
              "3          -0.249255        -0.521390        -0.321371        -0.321371\n",
              "4          -0.249255        -0.321371        -0.321371        -0.321371\n",
              "..               ...              ...              ...              ...\n",
              "145        -0.305526        -0.521390        -0.408088        -0.190701\n",
              "146        -0.305526        -0.047044        -0.408088        -0.329271\n",
              "147        -0.305526        -0.521390        -0.408088        -0.190701\n",
              "148        -0.305526        -0.321371        -0.408088        -0.190701\n",
              "149        -0.305526        -0.521390        -0.408088        -0.329271\n",
              "\n",
              "[150 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 112
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-Tsej61tiM3r"
      },
      "source": [
        "# Sum of each row\n",
        "iris['ans'] = iris.sum(axis=1)"
      ],
      "execution_count": 113,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 402
        },
        "id": "P8lQ_oq5iVCJ",
        "outputId": "5028295b-8c44-4f3c-e33c-328704a808e6"
      },
      "source": [
        "iris"
      ],
      "execution_count": 114,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>sepal_newLenght</th>\n",
              "      <th>sepal_newWeight</th>\n",
              "      <th>petal_newLenght</th>\n",
              "      <th>petal_newWeight</th>\n",
              "      <th>ans</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.563307</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>1.994671</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.563307</td>\n",
              "      <td>0.301030</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>1.818580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.563307</td>\n",
              "      <td>0.301030</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>1.818580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.563307</td>\n",
              "      <td>0.301030</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>1.818580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.563307</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>1.994671</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>145</th>\n",
              "      <td>0.494850</td>\n",
              "      <td>0.301030</td>\n",
              "      <td>0.390761</td>\n",
              "      <td>0.644612</td>\n",
              "      <td>1.831254</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>146</th>\n",
              "      <td>0.494850</td>\n",
              "      <td>0.897338</td>\n",
              "      <td>0.390761</td>\n",
              "      <td>0.468521</td>\n",
              "      <td>2.251470</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>147</th>\n",
              "      <td>0.494850</td>\n",
              "      <td>0.301030</td>\n",
              "      <td>0.390761</td>\n",
              "      <td>0.644612</td>\n",
              "      <td>1.831254</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>148</th>\n",
              "      <td>0.494850</td>\n",
              "      <td>0.477121</td>\n",
              "      <td>0.390761</td>\n",
              "      <td>0.644612</td>\n",
              "      <td>2.007345</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>149</th>\n",
              "      <td>0.494850</td>\n",
              "      <td>0.301030</td>\n",
              "      <td>0.390761</td>\n",
              "      <td>0.468521</td>\n",
              "      <td>1.655163</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>150 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "     sepal_newLenght  sepal_newWeight  ...  petal_newWeight       ans\n",
              "0           0.563307         0.477121  ...         0.477121  1.994671\n",
              "1           0.563307         0.301030  ...         0.477121  1.818580\n",
              "2           0.563307         0.301030  ...         0.477121  1.818580\n",
              "3           0.563307         0.301030  ...         0.477121  1.818580\n",
              "4           0.563307         0.477121  ...         0.477121  1.994671\n",
              "..               ...              ...  ...              ...       ...\n",
              "145         0.494850         0.301030  ...         0.644612  1.831254\n",
              "146         0.494850         0.897338  ...         0.468521  2.251470\n",
              "147         0.494850         0.301030  ...         0.644612  1.831254\n",
              "148         0.494850         0.477121  ...         0.644612  2.007345\n",
              "149         0.494850         0.301030  ...         0.468521  1.655163\n",
              "\n",
              "[150 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 114
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 282
        },
        "id": "jDsD2IgMPMyO",
        "outputId": "633f1c85-0107-4066-daab-a557fe3d871e"
      },
      "source": [
        "iris.boxplot(column=['ans'])"
      ],
      "execution_count": 116,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f999b7dbc10>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 116
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}